{"id":"W4200615498","doi":"10.1002/9781119794929.ch8","title":"Incorporating LP and Hybridizing It with Meta‐heuristic Algorithms","year":2021,"lang":"en","type":"other","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Heuristic; Linear programming; Convergence (economics); Algorithm; Meta heuristic; Mathematical optimization; Evolutionary algorithm; Computer science; Rate of convergence; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005582212,0.0004437755,0.0007780335,0.0004651273,0.0001552461,0.0009648658,0.0008553778,0.0001551434,0.003392104],"category_scores_gemma":[0.0002155893,0.0003314924,0.0000837594,0.000834042,0.0001849149,0.0001402428,0.0007742223,0.0003939993,0.00005141914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003240641,"about_ca_system_score_gemma":0.000440828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003660482,"about_ca_topic_score_gemma":0.00009506524,"domain_scores_codex":[0.996964,0.0002441049,0.0003682605,0.001086189,0.0009122908,0.0004252038],"domain_scores_gemma":[0.9979336,0.0002464732,0.0003062141,0.001025385,0.0002133084,0.0002750509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009290351,0.0003306137,0.00009232203,0.001445476,0.007312031,0.003454863,0.0003762542,0.0007214516,0.00004709179,0.09878237,0.7997347,0.08769354],"study_design_scores_gemma":[0.000876972,0.0001690548,0.0000154566,0.0004052228,0.0005422375,0.0004536583,0.000065472,0.6480969,0.0001263854,0.0007400763,0.3471137,0.001394952],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[1.083179e-7,0.00189349,0.6674766,0.0004797453,0.0001340406,0.0002482813,0.000007519362,0.0002374091,0.3295228],"genre_scores_gemma":[0.00001932572,0.0001243064,0.5981864,0.0002240631,0.0001184983,0.00003854098,0.00002233552,0.0001718401,0.4010947],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6473754,"threshold_uncertainty_score":0.9999137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05414899837175338,"score_gpt":0.2953488522267408,"score_spread":0.2411998538549875,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}